samsung SM-F966B
Geekbench AI Score
2083
Single Precision Score
2069
Half Precision Score
3333
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 29 2025 05:02 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966B |
| Model ID | samsung SM-F966B |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1500
278.9 IPS |
|
|
Image Classification (HP)
|
100% |
1707
317.4 IPS |
|
|
Image Classification (Q)
|
100% |
3872
720.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2151
34.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2148
34.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
4717
76.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
4317
5.04 IPS |
|
|
Pose Estimation (HP)
|
100% |
3869
4.51 IPS |
|
|
Pose Estimation (Q)
|
84% |
9054
10.7 IPS |
|
|
Object Detection (SP)
|
98% |
1034
82.3 IPS |
|
|
Object Detection (HP)
|
98% |
1220
97.1 IPS |
|
|
Object Detection (Q)
|
83% |
2909
235.0 IPS |
|
|
Face Detection (SP)
|
100% |
3735
44.4 IPS |
|
|
Face Detection (HP)
|
100% |
3709
44.1 IPS |
|
|
Face Detection (Q)
|
95% |
6966
83.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3873
29.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3000
23.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
5787
53.0 IPS |
|
|
Style Transfer (SP)
|
89% |
8651
11.2 IPS |
|
|
Style Transfer (HP)
|
89% |
8056
10.5 IPS |
|
|
Style Transfer (Q)
|
98% |
13198
17.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1451
53.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1712
63.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3515
130.2 IPS |
|
|
Text Classification (SP)
|
100% |
502
670.5 IPS |
|
|
Text Classification (HP)
|
99% |
597
797.3 IPS |
|
|
Text Classification (Q)
|
88% |
500
674.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1174
20.2 IPS |
|
|
Machine Translation (HP)
|
100% |
909
15.7 IPS |
|
|
Machine Translation (Q)
|
50% |
377
13.4 IPS |
